DETECTION OF INDUSTRIAL COMPONENTS WITH YOLOv3 MODEL

Abstract

This paper describes the general principles of machine learning, convolutional neural networks, and computer vision. It also outlines the process of creating a dataset for training, validation, and testing of artificial intelligence models. Based on this dataset, the problem of industrial component detection is addressed using a convolutional neural network. The objects for detection include pneumatic cylinders, distribution valves, and push buttons.